Research on Interval Constraint Range Domain Algorithm for 3D Reconstruction Algorithm Based on Binocular Stereo Vision

Author(s):  
Caiqing Wang ◽  
Shubin Wang ◽  
Enshuo Zhang ◽  
Jingtao Du
Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3666 ◽  
Author(s):  
Yue Wang ◽  
Xiangjun Wang ◽  
Zijing Wan ◽  
Jiahao Zhang

Nowadays, binocular stereo vision (BSV) is extensively used in real-time 3D reconstruction, which requires cameras to quickly implement self-calibration. At present, the camera parameters are typically estimated through iterative optimization. The calibration accuracy is high, but the process is time consuming. Hence, a system of BSV with rotating and non-zooming cameras is established in this study, in which the cameras can rotate horizontally and vertically. The cameras’ intrinsic parameters and initial position are estimated in advance by using Zhang’s calibration method. Only the yaw rotation angle in the horizontal direction and pitch in the vertical direction for each camera should be obtained during rotation. Therefore, we present a novel self-calibration method by using a single feature point and transform the imaging model of the pitch and yaw into a quadratic equation of the tangent value of the pitch. The closed-form solutions of the pitch and yaw can be obtained with known approximate values, which avoid the iterative convergence problem. Computer simulation and physical experiments prove the feasibility of the proposed method. Additionally, we compare the proposed method with Zhang’s method. Our experimental data indicate that the averages of the absolute errors of the Euler angles and translation vectors relative to the reference values are less than 0.21° and 6.6 mm, respectively, and the averages of the relative errors of 3D reconstruction coordinates do not exceed 4.2%.


2013 ◽  
Vol 415 ◽  
pp. 314-317
Author(s):  
Hui Yu Xiang ◽  
Baoan Han ◽  
Jia Jun Huang ◽  
Zhe Li

In order to realize the 3D reconstruction of stamping parts surface, this paper based on binocular stereo vision principle firstly introduces the model of the binocular cameras. Internal and external parameters of camera can be obtained by binocular calibration, taking the printed circle grid centers which are on the stamping parts as feature points, and then using the disparity image obtained by HALCON to reconstruct 3D information of the feature points. Finally, use Matlab to plot out the scatter diagram of feature points and the fitting curved surface diagram.


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